Analysis of HIV resistance mutations
DFG funded project within the DFG priority programInformatikmethoden zur Analyse und Interpretation großer genomischer Datenmengen
Informatikmethoden zur Analyse und Interpretation großer genomischer Datenmengen
Bioinformatics analysis of the relationship between mutations in the HIV genome and phenotypic drug resistance for antiviral therapy optimization
| Niko Beerenwinkel | Max Planck Institute for Informatics, Saarbrücken |
| Martin Däumer | Institute of Virology, University of Cologne |
| Daniel Hoffmann | Center of Advanced European Studies and Research, Bonn |
| Rolf Kaiser | Institute of Virology, University of Cologne |
| Joachim Selbig | Max Planck Institute of Molecular Plant Physiology, Golm |
Since HIV shows a very high genomic variability, even under the usual combination therapy consisting of several drugs, mutations occur, that confer resistance to the prescribed drugs and even to drugs not yet prescribed (cross-resistance). Therefore, physicians are faced with the problem of finding a new potent drug combination after therpy failure rather frequently.
Clinical trials have shown that therapy changes based on a genotypic resistance test (i. e. sequencing of PRO and RT) result in a significantly better therapy success. However, the relations between observed mutations, phenotypic resistance and therapy success are poorly understood so far.
The goal of the Arevir project is to develop bioinformatics methods that help to understand these connections and that contribute directly to therapy optimization.
In a database, set up in collaboration with university hospitals and virological institutes, clinical data, sequence data and phenotypic resistance data are collected. Machine learning methods are applied in order to identify the determinats of therapeutic failure and to predict effective drug combinations.
We have established a web service for the prediction of phenotypic drug resistance from genotypes (geno2pheno).